Instructions to use cloudyu/Yi-34Bx2-MoE-60B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cloudyu/Yi-34Bx2-MoE-60B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="cloudyu/Yi-34Bx2-MoE-60B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cloudyu/Yi-34Bx2-MoE-60B")
model = AutoModelForCausalLM.from_pretrained("cloudyu/Yi-34Bx2-MoE-60B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cloudyu/Yi-34Bx2-MoE-60B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cloudyu/Yi-34Bx2-MoE-60B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cloudyu/Yi-34Bx2-MoE-60B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cloudyu/Yi-34Bx2-MoE-60B

SGLang

How to use cloudyu/Yi-34Bx2-MoE-60B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "cloudyu/Yi-34Bx2-MoE-60B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cloudyu/Yi-34Bx2-MoE-60B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "cloudyu/Yi-34Bx2-MoE-60B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cloudyu/Yi-34Bx2-MoE-60B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cloudyu/Yi-34Bx2-MoE-60B with Docker Model Runner:
```
docker model run hf.co/cloudyu/Yi-34Bx2-MoE-60B
```

What are the merging parameters?

by rombodawg - opened Jan 11, 2024

Discussion

rombodawg

Jan 11, 2024

Can you upload the .yml either in this discussion, or prefferably add it to your model card of the merging parameters used in this merge, and your other merges. at the very least for this one

ehartford

Jan 11, 2024

can I please see the mergekit .yml?

Yhyu13

Jan 12, 2024

Sir, pls

MaziyarPanahi

Jan 14, 2024

I do agree that having reproducible steps would be great such as either mergekit .yml or some info regarding which methods/which layers etc.

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